1#!/usr/bin/env python3
2
3#            Copyright Hans Dembinski 2018 - 2019.
4#   Distributed under the Boost Software License, Version 1.0.
5#      (See accompanying file LICENSE_1_0.txt or copy at
6#            https://www.boost.org/LICENSE_1_0.txt)
7
8import os
9import numpy as np
10import glob
11import re
12import json
13import sys
14from collections import defaultdict, OrderedDict
15from matplotlib.patches import Rectangle
16from matplotlib.lines import Line2D
17from matplotlib.text import Text
18from matplotlib.font_manager import FontProperties
19import matplotlib.pyplot as plt
20import matplotlib as mpl
21
22mpl.rcParams.update(mpl.rcParamsDefault)
23
24cpu_frequency = 0
25
26data = defaultdict(lambda: [])
27for fn in sys.argv[1:]:
28    d = json.load(open(fn))
29    cpu_frequency = d["context"]["mhz_per_cpu"]
30    for bench in d["benchmarks"]:
31        name = bench["name"]
32        time = min(bench["cpu_time"], bench["real_time"])
33        m = re.match("fill_(n_)?([0-9])d<([^>]+)>", name)
34        if m.group(1):
35            time /= 1 << 15
36        tags = m.group(3).split(", ")
37        dim = int(m.group(2))
38        label = re.search(
39            "fill_([a-z]+)", os.path.splitext(os.path.split(fn)[1])[0]
40        ).group(1)
41        dist = tags[0]
42        if len(tags) > 1 and tags[1] in ("dynamic_tag", "static_tag"):
43            if len(tags) == 3 and "DStore" in tags[2]:
44                continue
45            label += "-" + {"dynamic_tag": "dyn", "static_tag": "sta"}[tags[1]]
46            label += "-fill" if m.group(1) else "-call"
47        data[dim].append((label, dist, time / dim))
48
49time_per_cycle_in_ns = 1.0 / (cpu_frequency * 1e6) / 1e-9
50
51plt.figure(figsize=(7, 6))
52i = 0
53for dim in sorted(data):
54    v = data[dim]
55    labels = OrderedDict()
56    for label, dist, time in v:
57        if label in labels:
58            labels[label][dist] = time / time_per_cycle_in_ns
59        else:
60            labels[label] = {dist: time / time_per_cycle_in_ns}
61    j = 0
62    for label, d in labels.items():
63        t1 = d["uniform"]
64        t2 = d["normal"]
65        i -= 1
66        z = float(j) / len(labels)
67        col = (1.0 - z) * np.array((1.0, 0.0, 0.0)) + z * np.array((1.0, 1.0, 0.0))
68        if label == "root":
69            col = "k"
70            label = "ROOT 6"
71        if "numpy" in label:
72            col = "0.6"
73        if "gsl" in label:
74            col = "0.3"
75            label = "GSL"
76        tmin = min(t1, t2)
77        tmax = max(t1, t2)
78        r1 = Rectangle((0, i), tmax, 1, facecolor=col)
79        r2 = Rectangle(
80            (tmin, i), tmax - tmin, 1, facecolor="none", edgecolor="w", hatch="//////"
81        )
82        plt.gca().add_artist(r1)
83        plt.gca().add_artist(r2)
84        font = FontProperties(size=9)
85        tx = Text(
86            -0.5,
87            i + 0.5,
88            "%s" % label,
89            fontproperties=font,
90            va="center",
91            ha="right",
92            clip_on=False,
93        )
94        plt.gca().add_artist(tx)
95        j += 1
96    i -= 1
97    font = FontProperties()
98    font.set_weight("bold")
99    tx = Text(
100        -0.5,
101        i + 0.6,
102        "%iD" % dim,
103        fontproperties=font,
104        va="center",
105        ha="right",
106        clip_on=False,
107    )
108    plt.gca().add_artist(tx)
109plt.ylim(0, i)
110plt.xlim(0, 80)
111
112plt.tick_params("y", left=False, labelleft=False)
113plt.xlabel("average CPU cycles per random input value (smaller is better)")
114
115plt.tight_layout()
116
117plt.savefig("fill_performance.svg")
118plt.show()
119